Generating auxiliary information for a media presentation

ABSTRACT

Techniques for generating auxiliary information for a media presentation are provided. In one example, a computer-implemented method comprises receiving, by a device operatively coupled to a processor, first feedback information for a group of users regarding mental states of the users during a media presentation. The computer-implemented method can further comprise determining, by the device, first parts of the media presentation considered confusing to at least some of the users and second parts of the media presentation considered interesting to at least some of the users based on the first feedback information, and generating, by the device, an index data structure comprising first information identifying the first parts and classifying the first parts as confusing and second information identifying the second parts and classifying the second parts as interesting.

BACKGROUND

The subject disclosure relates to generating auxiliary information for amedia presentation.

SUMMARY

The following presents a summary to provide a basic understanding of oneor more embodiments of the invention. This summary is not intended toidentify key or critical elements, or delineate any scope of theparticular embodiments or any scope of the claims. Its sole purpose isto present concepts in a simplified form as a prelude to the moredetailed description that is presented later. In one or moreembodiments, systems, computer-implemented methods, apparatus and/orcomputer program products that facilitate generating auxiliaryinformation for a media presentation are described.

According to an embodiment, a system is provided that can comprise amemory that stores computer-executable components and a processor thatexecutes computer-executable components stored in the memory. In one ormore implementations, the computer-executable components can comprise afeedback component that receives first feedback information for a groupof users regarding mental states of the users during a mediapresentation. The computer-executable components can further comprise ananalysis component that determines first parts of the media presentationconsidered confusing to at least some of the users and second parts ofthe media presentation considered interesting to at least some of theusers based on the first feedback information. The computer-executablecomponents can further comprise an index component that generates anindex data structure comprising: first information identifying the firstparts and classifying the first parts as confusing; and secondinformation identifying the second parts and classifying the secondparts as interesting.

According to another embodiment, a computer-implemented method isprovided. In one example, the computer-implemented method comprisesreceiving, by a device operatively coupled to a processor, firstfeedback information for a group of users regarding mental states of theusers during a media presentation. The computer-implemented method canfurther comprise determining, by the device, levels of confusionassociated with respective parts of the presentation and levels ofinterest associated with the respective parts of the presentation basedon the first feedback information. The computer-implemented method canfurther comprise classifying, by the device, first parts of therespective parts of the presentation as confusing based on the levels ofconfusion associated with the first parts being above a threshold levelof confusion. The computer-implemented method can further compriseclassifying, by the device, second parts of the respective parts of thepresentation as interesting based on the levels of interest associatedwith the second parts being above a threshold level of interest.

In yet another embodiment, a computer program for identifying respectiveparts of a media presentation considered confusing or interesting isdescribed. The computer program product comprises a computer readablestorage medium having program instructions embodied therewith, and theprogram instructions are executable by a processing component to causethe processing component to identify, based on feedback informationregarding facial expressions of users during a first presentation of themedia presentation to the users, first parts of the media presentationconsidered confusing to at least some of the users and second parts ofthe media presentation considered interesting to at least some of theusers. The program instructions can further cause the processingcomponent to generate an index data structure comprising firstinformation identifying the first parts and including respectiveclarifying information for the first parts, and second informationidentifying the second parts and including respective supplementaryinformation for the second parts.

DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example, non-limiting systemthat facilitates classifying content of a media presentation inaccordance with one or more embodiments described herein.

FIG. 2 presents a table of an example, non-limiting contentclassification index for a media presentation in accordance with one ormore embodiments described herein.

FIG. 3 illustrates a block diagram of an example, non-limiting userdevice that facilitates classifying content of a media presentation andgenerating auxiliary information for the content in accordance with oneor more embodiments described herein.

FIG. 4 illustrates a block diagram of an example, non-limiting systemthat facilitates classifying content of a media presentation andgenerating auxiliary information for the content in accordance with oneor more embodiments described herein.

FIG. 5 presents a table of an example, non-limiting auxiliaryinformation index for a media presentation in accordance with one ormore embodiments described herein.

FIG. 6 illustrates a block diagram of another example, non-limitingsystem that facilitates generating auxiliary information for a mediapresentation and conditional provisioning of the auxiliary informationin accordance with one or more embodiments described herein.

FIG. 7 illustrates a block diagram of an example, non-limiting systemthat facilitates refining auxiliary information generated for a mediapresentation in accordance with one or more embodiments describedherein.

FIGS. 8 and 9 illustrate flow diagrams of an example, non-limitingcomputer-implemented method that facilitates classifying content of amedia presentation in accordance with one or more embodiments describedherein.

FIG. 10 illustrates a block diagram of an example non-limiting operatingenvironment in which one or more embodiments described herein can befacilitated.

DETAILED DESCRIPTION

The following detailed description is merely illustrative and is notintended to limit embodiments and/or application or uses of embodiments.Furthermore, there is no intention to be bound by any expressed orimplied information presented in the preceding Background or Summarysections, or in the Detailed Description section.

The subject disclosure is directed to computer processing systems,computer-implemented methods, apparatus and/or computer program productsthat facilitate generating auxiliary information for a presentationbased on user feedback received during presentation to a group of users.The user feedback can be associated with users' reactions to respectiveparts of the presentation. One or more aspects of the auxiliaryinformation that is generated can later be provided to one or more newusers when one or more new users subsequently experience thepresentation. The presentation can include, for example, a live orrecorded educational, informative, or instructional presentation inwhich one or more presenters speak about a particular subject and/orprovide a visual demonstration related to the subject. For example, apresentation can include a live or recorded lecture presented by aprofessor to a group of students about atomic bonding while presentingand discussing a previously prepared slideshow on atomic bonding. Inanother example, a presentation can include a live or recorded audibledescription of different art included in a museum in association with awalking tour through the museum.

In particular, as a user is viewing, listening to or otherwise receivinga presentation via a user device, the user may be interested orintrigued by certain parts of the presentation, confused by certainparts of the presentation, bored with certain parts of the presentation,etc. When the presentation is experienced in a live environment,especially in a group setting, the user may be unable or too shy to askthe presenter questions associated with parts of the presentation theuser finds interesting or confusing. Similarly, the user may be unableor too shy to inform the presenter that the user considers certainsubject matter boring, not useful or otherwise not engaging in contextsin which the user or the presenter could elect to change the content ora part of the content of the presentation to different content the userwould likely find more interesting, useful or engaging. Likewise, whenexperiencing a presentation in a non-live context, such as watching avideo of a presentation, listening to an audio recording of apresentation, or clicking through a slideshow, the user may come acrosscontent the user finds interesting, confusing, boring, etc. However, theuser may not be inclined or able to stop the presentation and lookupadditional information (e.g., via searching sources on the Internet) orchange the presentation (e.g., stop the presentation entirely, skip oversome content etc.).

In accordance with one or more embodiments, the subject computerprocessing systems, computer-implemented methods, apparatus and/orcomputer program products facilitate classifying respective parts of apresentation based on user feedback generated during presentation of thepresentation to a group of users regarding their impressions ofdifferent parts of the presentation. For example, the feedback canindicate whether one or more of the users find a part of thepresentation confusing, interesting, boring, exciting, amusing, etc. Inone or more implementations, the feedback can include informationregarding respective mental states of one or more of the users duringthe presentation. In particular, techniques are provided forautomatically detecting a mental state of a user during a presentationand correlating the mental state with a particular part of thepresentation. In some implementations, the mental state of a user can bedetected based on facial expressions exhibited by the user during thepresentation. The facial expressions can indicate the user is confused,interested, bored, excited, amused, etc.

In one embodiment, the facial expressions are captured and/or detectedvia a heads-up display (HUD) device worn by the user or another deviceassociated with the user. In some embodiments, a user can also provideexplicit feedback regarding the user's impression of a particular partof a presentation. For example, the user can provide explicit input thatstates the user is confused, interested, bored etc. via the user devicein association with presentation of a particular part of a presentation.In various additional embodiments, dialogue performed between thepresenter and one or more of the users in the group during thepresentation can be used to identify parts of the presentation the auser considered confusing, interesting, boring, exciting, amusing, etc.

Based on user feedback received for a presentation regarding varioususers' aggregate impressions of respective parts of the presentation,the respective parts of the presentation can be classified as confusing,interesting, boring, exciting, amusing, etc. Based on theclassifications associated with the respective parts of thepresentation, auxiliary information can be generated and associated withthe respective parts of the presentation. The type of auxiliaryinformation that is associated with a part of the presentation can varybased on the classification associated therewith. For example, auxiliaryinformation for a first part of a presentation classified as confusingcan include clarifying information intended to clarify the confusionassociated with the first part of the presentation. In another example,a second part of the presentation classified as interesting can beassociated with supplementary auxiliary information that providessupplementary detailed examples and/or applications associated with thesecond part of the presentation.

In some implementations, different versions of the auxiliary informationcan be tailored to different user traits or preferences, such asdifferent learning styles, educational levels, intellectual levels orabilities, reading levels, etc. The different versions can vary in thetype of content of the auxiliary information, which can include, but isnot limited to, text, images, video, audio and hyperlinks. The differentversions can also vary with respect to an amount of content, a degree ofcomplexity of the content, an intellectual level associated with thecontent, and the like. According to these embodiments, in addition togenerating auxiliary information for a part of a presentation related toa mental state associated with the part, a particular version of theauxiliary information can be generated based on a trait or preference ofthe user that exhibited the mental state and/or based on a trait orpreference of another user to whom the auxiliary information may laterbe provided.

In various embodiments, information classifying respective parts of thepresentation as confusing, interesting, boring, exciting, amusing, etc.,can be stored in an index data structure and associated with thepresentation. The index data structure can also include informationidentifying auxiliary information entries that have been generated andprovided for the respective parts of the presentation. When thepresentation is subsequently presented to a new user, new feedbackinformation can be received from the new users regarding the new user'sindividual impression to respective parts of the presentation, and theindex data structure can be employed to automatically identify, retrieveand provide auxiliary information to the new user (e.g., at a userdevice of the new user) based on the new user's individual impressionsof the respective parts of the presentation. For example, based on adetermination that the new user is confused about topic 2 of apresentation, a determination can be made as to whether clarifyingauxiliary information has been obtained at the index data structure fortopic 2 of the presentation. In response to a determination thatclarifying information has been obtained (and stored) for topic 2, theclarifying information can be retrieved and provided to the new user.

The various features and functionalities of the disclosed computerprocessing systems, computer-implemented methods, apparatus and/orcomputer program products facilitate automatically providing auxiliaryinformation to user devices while a user is viewing, listening to, orotherwise experiencing a presentation. The auxiliary information can beprovided when desired or needed as determined based on implicit (e.g., adetermined mental state) or explicit (e.g., a direct request for theauxiliary information) feedback detected at the user device during thepresentation. Accordingly, a plurality of users can view or experiencethe same presentation in a live or non-live setting and receivedifferent auxiliary information at different times during thepresentation based on their individual responses to different parts ofthe presentation and/or based on their individual traits andpreferences. Therefore a same presentation can be tailored to the needsand preferences of different users (in some embodiments, in real-time orsubstantially real-time) as the respective users experience thepresentation, thus enabling various users to experience the presentationin a more fulfilling and enjoyable manner.

One or more embodiments are now described with reference to thedrawings, wherein like referenced numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea more thorough understanding of the one or more embodiments. It isevident, however, in various cases, that the one or more embodiments canbe practiced without these specific details.

FIG. 1 illustrates a block diagram of an example, non-limiting system100 that facilitates classifying content of a presentation in accordancewith one or more embodiments described herein. Aspects of systems (e.g.,system 100 and the like), apparatuses or processes explained in thisdisclosure can constitute machine-executable component(s) embodiedwithin machine(s), e.g., embodied in one or more computer readablemediums (or media) associated with one or more machines. Suchcomponent(s), when executed by the one or more machines, e.g.,computer(s), computing device(s), virtual machine(s), etc. can cause themachine(s) to perform the operations described.

One or more implementations of the system 100 and/or the components ofthe system 100 can provide substantial improvements to live and Internetbased learning systems by generating an auxiliary information index thatincludes information identifying respective parts of a presentationconsidered confusing and interesting to users and associating definedauxiliary information with the respective parts. As a result, thesubject systems can automatically provide users with auxiliaryinformation related to a presentation in real-time or substantiallyreal-time based on the users' mental and emotional states andpreferences. Accordingly, a plurality of users can view or experiencethe same presentation in a live or non-live setting and receivedifferent auxiliary information at different times during thepresentation based on their individual responses to different parts ofthe presentation and/or their individual traits and preferences.Therefore, the same presentation can be dynamically and automaticallytailored to the needs and preferences of different users in real-time asthe respective users experience the presentation, thus enabling eachuser to experience the presentation in a more fulfilling and enjoyablemanner.

The system 100 and/or the components of the system 100 can be employedto use hardware and/or software to solve problems that are highlytechnical in nature, that are not abstract and that cannot be performedas a set of mental acts by a human. For example, system 100 and/or thecomponents of the system 100 can be employed to use hardware and/orsoftware to perform operations including affective computing related toautomatically detecting and recognizing emotional information,correlating the emotional information with presentation contentassociated with causation of a specific mental state, and automaticallyselecting and providing auxiliary information for the presentationcontent. Further, some of the processes performed may be performed byspecialized computers for carrying out defined tasks related to theperforming affective computing to facilitate receiving and correlatingemotional state information with respective parts of a presentation toautomatically determine parts of a presentation that are consideredconfusing or interesting. System 100 and/or components of the system 100can be employed to solve new problems that arise through advancements intechnology, computer networks, the Internet and the like. System 100 canfurther provide technical improvements to live and Internet basedlearning systems by improving processing efficiency among processingcomponents associated with selecting and providing auxiliary informationassociated with a presentation in real-time based a user's currentmental state and preferences using an auxiliary information index.

As shown in FIG. 1, system 100 can include a presentation server device102, one or more networks 124 and one or more user devices 126. Thepresentation server device 102 can include various computer-executablecomponents, including, but not limited to, server feedback component104, analysis component 106, index component 114 and servercommunication component 116. The presentation server device 102 can alsoinclude or otherwise be associated with at least one memory 120 thatstores computer-executable components (e.g., the server feedbackcomponent 104, the analysis component 106, the index component 114, andthe server communication component 116). The presentation server device102 can also include or otherwise be associated with at least oneprocessor 118 that executes the computer-executable components stored inthe memory 120. The presentation server device 102 can further include asystem bus 112 that can couple the various components including, but notlimited to, the server feedback component 104, the analysis component106, the index component 114, the server communication component 116,the memory 120 and/or the processor 118.

In various embodiments, the presentation server device 102 and the oneor more user devices 126 can operate in a server/client relationshipwherein auxiliary information associated with a presentation is providedby the presentation server device 102 to the one or more user devices126 based on processing, by the presentation server device 102 and/orthe one or more user devices 126, of feedback information regarding theneed or desire for the auxiliary information by respective usersassociated with the one or more user devices 126. In someimplementations, the presentation server device 102 and the one or moreuser devices 126 can be communicatively connected via one or morenetworks 124. Such networks 124 can include wired and wireless networks,including, but not limited to, a cellular network, a wide area network(WAN) e.g., the Internet) or a local area network (LAN). For example,the one or more user devices 126 can communicate with presentationserver device 102 (and vice versa) using virtually any desired wired orwireless technology, including but not limited to: wireless fidelity(Wi-Fi), global system for mobile communications (GSM), universal mobiletelecommunications system (UMTS), worldwide interoperability formicrowave access (WiMAX), enhanced general packet radio service(enhanced GPRS), third generation partnership project (3GPP) long termevolution (LTE), third generation partnership project 2 (3GPP2) ultramobile broadband (UMB), high speed packet access (HSPA), Zigbee andother 802.XX wireless technologies and/or legacy telecommunicationtechnologies, BLUETOOTH®, Session Initiation Protocol (SIP), ZIGBEE®,RF4CE protocol, WirelessHART protocol, 6LoWPAN (IPv6 over Low powerWireless Area Networks), Z-Wave, and/or an ultra-wideband (UWB) standardprotocol.

For example, in one embodiment, one or more user devices 126 can berespectively associated with students located in relatively closeproximity to the presentation server device 102 (e.g., within the samephysical classroom space). According to this embodiment, the one or moreuser devices 126 and the presentation server device 102 can becommunicatively connected via an area network (e.g., LAN). In anotherembodiment, the one or more user devices 126 can be respectivelyassociated with students located in disparate remote physical locationsrelative to the presentation server device 102. According to thisembodiment, the one or more user devices 126 and the presentation serverdevice 102 can be communicatively connected via a WAN (e.g., a cellularnetwork, the Internet, etc.). In an aspect, one or more components ofsystem 100 can interact via disparate networks.

The presentation server device 102 can include server communicationcomponent 116 to facilitate wireless communication between thepresentation server device 102 and the one or more user devices 126,and/or between the presentation server device 102 and one or more otherexternal devices (not shown). For example, the server communicationcomponent 116 can receive feedback information from one or more userdevices 126 and/or one or more other devices (e.g., a remote camera,sensors worn by the user, etc.) and forward the feedback information tothe server feedback component 104 for processing. The servercommunication component 116 can also send auxiliary information to theone or more user devices 126 for rendering at the respective userdevices in association with viewing, listening to, or otherwiseexperiencing a presentation. In some embodiments, the servercommunication component 116 can also send presentation data to the oneor more user devices. For example, the server communication component116 can send slides included in a slideshow component of a presentationfor rendering at the respective user devices. In another example inwhich the presentation includes a video, the server communicationcomponent 116 can send the video to the respective user devices. In yetanother example in which the presentation includes an audio recording,the server communication component 116 can send the audio recording tothe respective user devices.

In some embodiments, the server communication component 116 can stream apresentation to the one or more user devices 126. For an example, in anembodiment in which the presentation includes a live or recorded videoand/or audio, the server communication component 116 can stream the liveor recorded video and/or audio to the one or more user devices 126. Theserver communication component 116 can be or include hardware (e.g., acentral processing unit (CPU), a transceiver, a decoder), software(e.g., a set of threads, a set of processes, software in execution) or acombination of hardware and software that facilitates communicatinginformation between the presentation server device 102 and the one ormore user devices 126. Although in system 100 various components (e.g.,the server feedback component 104, the analysis component 106, the indexcomponent 114, and the server communication component 116) are providedon a server device (e.g., a presentation server device 102), in otherembodiments, any number of different types of devices can be associatedwith or include the aforementioned components. All such embodiments areenvisaged. Further, although in the embodiment shown the server feedbackcomponent 104, the analysis component 106, the index component 114, andthe server communication component 116 are provided at the presentationserver device 102, it should be appreciated that the architecture ofsystem 100 is not so limited. For example, one or more of the componentsincluded at the presentation server device 102 can be located at anotherdevice, such as another server device, an intermediary device betweenthe server device and the one or more user devices 126, or at the one ormore user devices 126, etc.

The one or more user devices 126 can include any suitable computingdevice associated with a user and that can receive and render auxiliaryinformation associated with a presentation provided by the presentationserver device 102. In some implementations, the one or more user devices126 can also facilitate capturing feedback information regarding therespective users' need or desire for the auxiliary information andproviding the feedback information to the presentation server device 102(e.g., as discussed infra with respect to FIG. 3). For example, the oneor more user devices 126 can include a desktop computer, a laptopcomputer, a television, an Internet enabled television, a mobile phone,a smartphone, a tablet user computer (PC), a digital assistant (PDA), aHUD, a virtual reality (VR) headset, an augmented reality (AR) headset,or another type of wearable computing device. As used in thisdisclosure, the terms “user,” “teacher,” “student,” “presenter,”“presentee,” and the like refer to a person, entity, system, orcombination thereof that can employ system 100 (or additional systemsdescribed in this disclosure) using a user device of the one or moreuser devices 126 or the presentation server device 102.

In various embodiments, the presentation server device 102 facilitatesclassifying content of a media presentation based on user feedback. Theterm “media presentation” is used herein to describe a live or recorded(e.g., an audio recording, a video recording, or a video recordingincluding audio) presentation that includes a visual component, an audiocomponent, or both a visual and an audio component. In variousimplementations, the media presentation can be educational, informativeor instructive in nature. For example, a media presentation can includea live or recorded lecture presented by a teacher to group of students.In some implementations, the live or recorded lecture can be presentedin association with a slideshow having a sequence of slides, such asslideshow presentation created using POWERPOINT® or a similar softwareapplication. The information included in the respective slides caninclude text, charts, images, video, audio, hyperlinks, or the like. Inanother example, a media presentation can include a live or recordeddemonstration performed by one or more people. For instance, a mediapresentation can include a live or recorded presentation of anexperiment (e.g., a laboratory experiment), a procedure (e.g., asurgical procedure), or an activity (e.g., cooking, snowboarding). Inanother example, a media presentation can include a live or recordedpresentation in which one or more presenters describe and/or demonstratehow to do an activity (e.g., a “how-to” video). In yet another example,a media presentation can include a live or recorded presentation inwhich a tour guide walks through a museum and provides informativeinformation about different art pieces in the museum. Still in anotherexample, a media presentation can include an audio recording of the tourthrough the museum. According to this example, the audio recording canbe listened to by museum visitors using headphones associated via awearable device as they walk through the museum and auxiliaryinformation can be rendered via the wearable device based feedbackreceived from the respective visitors in association with presentationof the audio recording.

In order to facilitate classifying content of a media presentation, thepresentation server device 102 can include server feedback component 104to receive feedback information for a group of users regarding theirimpressions of respective parts of the media presentation. In one ormore embodiments, this feedback information can include informationregarding mental states of users over the course of the presentation.For example, in association with viewing, listening to or otherwiseexperiencing a presentation, the server feedback component 104 canreceive feedback information for a user that indicates the user isintrigued or particularly interested, confused, bored or unengaged,amused, excited, concerned or worried, offended, etc. The analysiscomponent 106 can further correlate respective mental states of theusers with respective parts of the presentation associated withcausation of the respective mental states to classify the respectiveparts as confusing, interesting, exciting, boring, etc. In someimplementations, feedback regarding a mental state of a user can bebased on one or more facial expressions expressed by the user during thepresentation. For example, system 100 can employ various existingemotion recognition technologies that can determine a user's mental oremotional state based on analysis of facial expressions and/or eyemovement of the user captured in video or one or more images of theuser. With facial emotion detection, algorithms can detect faces withina photo or video, and sense micro expressions by analyzing therelationship between points on the face, based on curated databasescompiled in academic environments. According to these implementations,as a user is viewing, listening to, or otherwise experiencing apresentation via a user device, facials expressions and/or eye movementsof the user can be captured and/or detected via one or more user facingcameras. For example, in some embodiments, the user can wear a HUDdevice including a user facing camera or image sensor that can capturefacial expressions and/or eye movements of the user during apresentation. In another example, a user facing camera can be includedon a device such as a tablet, smartphone, desktop or laptop computeremployed by the user and capture facial expressions and/or eye movementsof the user during a presentation. In another example, an external userfacing camera can be included in a same room as the user or a group ofusers and capture facial expressions and/or eye movements of therespective users. In some embodiments, the user facing camera or camerascan be or be provided at the one or more user devices 126 associatedwith the respective users at which auxiliary information for thepresentation is rendered.

In various embodiments, image data of a user face during a presentationcan be captured and processed to determine a mental state of the user inreal-time or substantially real-time. As used herein, the term“real-time” can mean processing and capturing to determine the mentalstate within a defined number of minutes or seconds (e.g., within 10seconds, within 30 seconds, within 60 seconds, within 2 minutes) afterthe image data is generated. Accordingly, as the user is viewing,listening to, or otherwise experiencing a presentation, one or moremental states of the user over the course of the presentation can bedetermined in real-time or substantially real-time. In some embodiments,captured facial expressions and/or eye movements can be processed by thecapture device (e.g., a user device of the one or more user devices 126or another device) that captured the respective facial expressionsand/or eye movements to determine a mental or emotional state of theuser. The capture device can further send feedback informationidentifying the determined mental or emotional state of the user to thepresentation server device 102 in real-time or substantially real-time.According to these embodiments, the server feedback component 104 canreceive information that identifies respective mental states of the userover the course of a presentation in real-time or substantiallyreal-time. For example, in one embodiment, a camera or image sensor canbe included at a user device associated with a user (e.g., a user deviceof the one or more user devices 126). The user device can capture (e.g.,via the camera or image sensor) and process facial expressions and/oreye movements of the user during the presentation to determine a mentalstate of the user (e.g., interested, confused, excited, bored, amused,offended, etc.). The user device can further provide informationidentifying the mental state of the user to the presentation serverdevice 102 in real-time or substantially real-time (in response tocapture and processing). In other embodiments, image data of a user facecaptured during a presentation (e.g., by a camera or image sensor at theuser device or another device) can be sent to the presentation serverdevice 102 by the capture device for processing by the server feedbackcomponent 104. For example, a user device (e.g., a HUD device, a tablet,a laptop computer, a desktop computer, etc.) associated with a userexperiencing a presentation can capture image data of the user faceduring the presentation and send the image data (e.g., in real-time orsubstantially real-time) to the presentation server device 102 forprocessing by the server feedback component 104. According to theseembodiments, the server feedback component 104 can receive image data(e.g., video or still images) captured of a user face during apresentation and process the image data to determine respective mentalor emotional states of the user during the presentation in real-time orsubstantially real-time.

In various additional embodiments, feedback information regarding amental or emotional state of a user during a presentation can bedetermined based on analysis of speech spoken by the user during thepresentation. According to these embodiments, the user device employedby the user, the presentation server device 102, or another devicewithin audible range of the user can include audio recording hardwareand software to record and analyze speech spoken by the user during apresentation. For example, the speech can include a question raised bythe user. In another example, the speech can include dialogue betweenthe user and the presenter or between the user and another user. In someimplementations, analysis of the speech can include analysis of tone andword content using one or more sonic algorithms to determine a mental oremotional state of the user during the presentation. Similar to theimage data, the server feedback component 104 can receive processedspeech data from the capture device associated with capture of themotion data (e.g., the user device of the one or more user devices 126,the presentation server device 102, or another device) identifying amental or emotional state of the user based on the speech data, and/orreceive raw speech data from the capture device for processing by theserver feedback component 104 to determine the mental or emotional stateassociated with the speech data. In another embodiment, feedbackinformation regarding a mental or emotional state of a user during apresentation can be determined based on analysis of body movement orgestures of the user during the presentation. For example, motioninformation regarding movement and motion of the user during apresentation can be captured and analyzed to identify gestures or bodylanguage indicative of different emotional states of the user during thepresentation. According to this embodiment, in one aspect, one or moremotion sensors can be worn by the user or be included in a device wornby the user (e.g., the user device of the one or more user devices 126or another device) and capture motion data regarding motion or movementof the user during the presentation (e.g., gestures, fidgeting,remaining relatively still, changing a body position, blinking, foottapping, etc.). In another expect, information regarding user motionduring presentation can be discerned from image data (e.g., video)captured of the user during the presentation. The server feedbackcomponent 104 can further receive processed motion data from the capturedevice associated with capture of the motion data (e.g., a user deviceof the one or more user devices 126 or another device) identifying amental or emotional state of the user based on the motion data, and/orreceive raw motion data for processing by the server feedback component104 to determine the mental or emotional state associated with themotion data.

In another embodiment, feedback information regarding a mental oremotional state of a user during a presentation can be determined basedon analysis of biometric data captured from the user during thepresentation. For example, the biometric information can include, but isnot limited to, information regarding the user's heart rate, respiratoryrate, muscle tension, and hormone levels (e.g., cortisol, oxytocin,acetylcholine, dopamine, serotonin, gaba, glutamine, endorphin,epinephrine, norepinephrine, and glutamate). According to thisembodiment, one or more biometric sensors can be worn by the user (e.g.,external to the body and/or internal to the body), and/or be included ina device worn by the user (e.g., a user device of the one or more userdevices 126 or another device) and biometric data associated with theuser during the presentation. The server feedback component 104 canfurther receive processed biometric data from the capture deviceassociated with capture of the biometric data (e.g., the user device)identifying a mental or emotional state of the user based on thebiometric data, and/or receive raw biometric data for processing by theserver feedback component 104 to determine the mental or emotional stateassociated with the biometric data.

In addition to determining a user's mental state based on feedbackinformation including one or more facial expressions of the user, speechof the user, motion of the user and/or biometric information of the userreceived in response to the presentation, the server feedback component104 can also receive explicit user feedback regarding a user'simpression of particular parts of a presentation. For example, as theuser is viewing, listening to or otherwise experiencing a presentation,the user can provide the server feedback component 104 direct input(e.g., via the user's user device 126) identifying a mental reaction ofthe user to a particular part of a presentation (e.g., input identifyingthe user as being confused, interested, bored, excited, etc). Forexample, the user device (e.g., a user device of the one or more userdevices 126 or another device) can include a suitable input mechanism(e.g., selection of a hard or soft button, a touch screen, a keypad, akeyboard, a mouse, voice input, gesture input, etc.) via which the usercan provide direct input indicating a mental state of the user (e.g.,input stating or meaning “I'm confused”). For example, the user canselect a hard or soft button on the user device, provide verbal ortextual input, perform a gesture or generate another defined signal thatcan be received by the server feedback component 104 and indicate theuser is confused about a particular part of the presentation. Similarly,the user can select a different button on the user device, providedifferent verbal or textual input, perform a different gesture, orgenerate a different defined signal that can be received by the serverfeedback component 104 and indicate the user is interested in aparticular part of the presentation and would like some clarifyinginformation. In some embodiments in which the presentation is a livepresentation, the server feedback component 104 can also receivefeedback information regarding dialogue associated with the livepresentation. For example, the dialogue can include dialogue between thepresenter and one or more users experiencing the presentation, referredto herein as a “presentee.” The dialogue can also include dialoguebetween two or more presentees. For instance, in a live presentationtaking place in a classroom environment in which a teacher is presentinga lecture to a group of students, at various times throughout the class,dialogue can include question and answer sessions between students andthe teacher as well as discussions between students. According to theseembodiments, the presentation server device 102 can include suitableaudio recording hardware and software to record audio during apresentation. In other embodiments, an audio recording of thepresentation can be captured by a device external to the presentationserver device 102 (e.g., a user device or another device) and providedto the server feedback component 104.

In one or more embodiments, the analysis component 106 can analyzereceived feedback associated with a presentation to identify andclassify respective parts of the presentation associated with thefeedback. In particular, the analysis component 106 can include contentassociation component 108 to correlate feedback indicating a particularmental state of a user (e.g., interested, confused, bored, excited,amuse, not amused, etc.) with a specific part of the content included inthe presentation that is or was being presented at the time the feedbackis received or within a defined amount of time after the feedback isreceived. The content association component 108 can also correlatedialogue (e.g., student-teacher interaction) during the presentationwith respective parts of the presentation (e.g., respective topics,sub-topics, elements, slides, etc.). For instance, in one or moreembodiments, the presentation server device 102 can have access toinformation identifying content included in a prior showing of thepresentation (e.g., in memory 120 or at another device). For example, inembodiments in which the presentation is a live presentation, thepresentation server device 102 can have access to information (e.g., anoutline) that identifies different topics and sub-topics to be discussedin the presentation and content respectively associated with thedifferent topics and sub-topics. In another example in which thepresentation includes a live or recorded presentation that includes aslideshow, the presentation server device 102 can have access toinformation identifying content included in respective slides of theslideshow and/or content associated with different parts or elements ofa single slide.

In some embodiments, the content association component 108 can determinea part of the content included in a presentation that is associated withreception of user feedback based on timing of reception of the feedbackand a current time point or time frame associated with the presentation.For example, the presentation can include a live or recordedpresentation associated with a known duration wherein particular partsor content included in the presentation are associated with known timepoints or time frames over the duration of the presentation. Forexample, with respect to a presentation including a plurality of knowntopics identified as topic 1, topic, 2, topic 3, etc., each (or, in someembodiments, one or more) of the different topics can be associated withknown time points or time frames throughout the presentation.Information regarding content respectively associated with differenttime points or time frames of the presentation can be stored in memory120 or otherwise accessible to the content association component 108.Accordingly, the content association component 108 can determine a timepoint or time frame of the presentation associated with reception ofparticular feedback (e.g., a user mental state and/or dialogue). Forexample, in some implementations, the presentation server device 102 canreceive information identifying the start time of the presentation andtrack the presentation time following the start of the presentation todetermine a time in the presentation when the feedback is or wasreceived. In some embodiments, in which the presentation includes avideo, the presentation server device 102 can play the video or streamthe video to the user devices 126 of the users and thus easily correlatereceived feedback from the user with a current time point or time frameof the video. The content association component 108 can further identifythe particular content of the presentation (e.g., topic 1, topic, 2,topic, 3, etc.) associated with that time point or time frame.

In another embodiment in which the presentation includes a slideshow,the content association component 108 can have access to information(e.g., stored in memory 120 or at another device) identifying content ofthe presentation respectively associated with each slide (or, in someembodiments, with one or more slides). The content association component108 can further determine or receive information identifying a currentslide that is or was being presented during a presentation at a timewhen the feedback is or was received (e.g., including mental statefeedback and dialogue feedback). For example, in some embodiments, thepresentation server device 102 can provide or render the respectiveslides and thus have direct knowledge about what slide is or was beingpresented when particular feedback is or was received. In someimplementations, the content association component 108 can further haveaccess to information identifying sub-topics or elements in a same slideand determine the particular sub-topic or element of a same slide thatis being presented at the time feedback is received. For example, theslides can include interactive slides in which different elements orparts of a single slide can be activated or highlighted. According tothis implementation, the content association component 108 can determinethe particular sub-topic or element being presented at the time feedbackis or was received based on information indicating a particular part orelement of the slide is being pointed to, highlighted, selected orotherwise activated.

Still in other embodiments, the presentation server device 102 caninclude or have access to information associating known keywords in apresentation with specific parts of the content of the presentation.According to these embodiments, the server feedback component 104 canreceive or determine information identifying a known keyword or keywordsthat are spoken during the presentation at a time associated withreception of feedback (e.g., including user mental state feedback anddialogue feedback). For example, in embodiments in which thepresentation server device 102 is located within audible range of thepresenter, the presentation server device 102 can include or employspeech recognition hardware and software to capture speech spoken by thepresenter and identify keywords spoken throughout the presentation. Thecontent association component 108 can further determine a keyword orkeywords spoken at a particular time or within a defined amount of timeafter reception of the feedback and further correlate the feedback withthe known part of the content associated with the keyword or keywords.In other embodiments, the user device associated with the user (e.g., auser device of the one or more user devices 126 or another device) caninclude the speech recognition hardware and/or software and determinethe keyword or keywords being presented at a time when the usergenerates or provides the feedback regarding the user's mental state orexplicit need or desire for auxiliary information. According to theseembodiments, the user device can include information identifying thekeyword or keywords in association with providing the feedbackinformation to the server feedback component 104.

Still in other embodiments, the content association component 108 cananalyze recorded audio of a presentation to identify and characterizedifferent parts of a presentation and to associate user feedback withthe different parts. For example, in embodiments in which thepresentation server device 102 has limited or no knowledge regarding thecontent of a presentation before the presentation is initiallypresented, the content association component 108 can employ suitablespeech analysis hardware and software provided at the presentationserver device 102 to identify keywords associated with respective partsof the presentation for which feedback is received (e.g., includingfeedback regarding mental states of users and/or dialogue associatedwith the presentation). The content association component 108 can thengenerate information identifying the keys words and associating thekeywords with received feedback. For example, in some implementations,the presenter can state a title of a particular topic of a presentationand the content association component 108 can identify feedback that isor was received shortly after announcing of the topic title and generateinformation associating that feedback with the topic title. In anotherexample, the content association component 108 can identify clusters ofrelated words associated with specific feedback indicating a pluralityof users are confused, interested, excited, bored, etc. The relatedwords can be grouped and considered a particular topic or part of thepresentation. The content association component 108 can further generateinformation associating the cluster of related words with the specificuser feedback. The content association component 108 can also identifypauses or breaks in the presentation recording and employ these pausesor breaks to identify different parts or topics of the presentation. Forexample, the content association component 108 can determine subjectmatter discussed after a pause or break to be a new topic or sub-topic.Thus in essence, the content association component 108 can determinewhat the presenter was talking about when presentees provided feedbackindicating they were confused, interested, bored, excited, etc. and/orwhen dialogue ensued, and generate information identifying what thepresenter was talking about with the feedback.

The content classification component 110 can analyze informationdeveloped by the content association component 108 associating receivedfeedback with different parts of a presentation to classify thedifferent parts of the presentation. In one or more embodiments, thedifferent parts of the presentation can be classified to reflect thecollective (or, in various embodiments, average or majority) sentimentof the group of users as reflected in their feedback. For example, thecontent classification component 110 can classify a part of apresentation as confusing, interesting, boring, exciting, amusing, etc.For example, in one or more implementations, for a defined part of thepresentation, the content classification component 110 can determine acollective (or, in various embodiments, an average or majority) userimpression of the part of the presentation based on the most prominentmental state associated with the part of the presentation. According tothis example, classification of the part of the presentation willreflect the mental state of the majority of users in the group. Forexample, in a classroom setting including 10 students, if 6 of thestudents expressed confusion for a part of the presentation, 2 of thestudents expressed interest, and 2 of the students expressed interest,the content classification component 110 can classify the part of thepresentation as confusing.

In some implementations, the content classification component 110 canfurther determine a degree to which respective users considered a partof a presentation confusing, interesting, boring, exciting, amusing,etc., based on the distribution of mental states associated with the parof the presentation. The content classification component 110 candetermine and associate a score (e.g., with respect to an arbitraryscale) with the part of the presentation indicating the degree. Forexample, the content classification component 110 can score a part of apresentation classified as confusing, interesting, boring, amusing,etc., based on a percentage of the mental states indicating confusion,interest, boredom, amusement, etc. According to this example, thegreater the percentage, the higher the score. For instance, infurtherance to the example, above, the part of the presentationconsidered confusing can be associated with a score of 6, 6/10 or 60%.

In various embodiments, rather than classifying a part of a presentationwith a single classification, the content classification component 110can associate information with respective parts of the presentation thatindicates a degree to which some of the users found it confusing,interesting, boring, exciting, amusing, etc. For example, user feedbackassociated with a part of a presentation can indicate that some usersfound the part of the presentation confusing while other users found itinteresting. Thus according to some embodiments, the contentclassification component 110 can associate two or more classificationswith a part of a presentation regarding two or more mental statesassociated with the part of the presentation wherein each classificationis associated with a score indicating the percentage of users that hadthe respective mental states in association with the part of thepresentation. In some embodiments, the content classification component110 can have access to information identifying character traits and/orpreferences associated with respective presentees from which feedback isreceived. For example, the respective presentees can be associated withuser profiles including whether the user prefers visual auxiliaryinformation or textual auxiliary information. In another example, theprofile information can indicate whether the user prefers complexauxiliary information, simple auxiliary information, short auxiliaryinformation, long auxiliary information, etc. With regards toeducational presentations, the user profile information can include, butis not limited to, information regarding a user's intellectual level orcapability (e.g., intelligence quotient (IQ)), grades, learning type(e.g., visual, mathematical, kinesthetic, auditory, etc.), reading levelor speed of the user, degree of background knowledge in the presentationsubject matter, multitasking ability, and the like. According to theseembodiments, in addition to classifying a part of a presentation withinformation indicating a mental state associated with the presentationand/or a level or degree of user that exhibited the mental state, thecontent classification component 110 can further determine one or moretraits or preferences of the users that exhibited that mental state. Forexample, the content classification component 110 can associateinformation with a part of a presentation indicating 60% of the usersfound it confusing and a majority of these users are visual learners. Inanother example, the content classification component 110 can associateinformation with a part of a presentation indicating users having anintellectual level above a threshold level (e.g., an IQ above 100) foundthis part of the presentation very interesting.

In one or more embodiments, the content classification component 110 canfurther employ information regarding dialogue associated with respectiveparts of a presentation to further facilitate classifying the respectiveparts of the presentation. For example, the content classificationcomponent 110 can determine that mental state feedback shows manystudents are confused about a particular part of a presentation and thisis corroborated by the fact that dialogue was initiated by one or moreusers for or during the part of the presentation. According to theseembodiments, the content classification component 110 can classify apart of a presentation as highly consuming, highly interesting, highlyexciting, etc., based on association of dialogue with the part, theduration of the dialogue, and/or an amount of questions associated withthe dialogue. The content classification component 110 can furtheranalyze feedback regarding mental states of presentees associated withthe part of the presentation corresponding to the dialogue to determinea particular mental state associated with the part of the presentation.

According to these embodiments, parts of the presentation associatedwith dialogue can be considered either more interesting and/or moreconfusing than other parts of the presentation for which dialogue wasnot initiated. For example, dialogue between a presentee and a presenterduring a live presentation generally can be initiated by a question orremark made by the presentee or the presenter. Generally, when apresentee poses a question to the presenter, the presentee may be eitherconfused about the subject matter being presented and/or desirous ofclarification or interested in the subject matter being presented anddesirous of additional information. Accordingly, parts of a presentationthat are associated with dialogue between the presentee and thepresenter that begin with a question being raised by a presentee can bedistinguished as interesting or confusing. Similarly, when a presenterposes a question for answering by a presentee, information can begleaned from the answers provided by the presentee as to whether thepresentee understands the subject matter in question. In someimplementations, the content classification component 110 can furtherdetermine parts of the presentation that are associated with a greateramount or duration of dialogue than other parts of the presentation. Forexample, parts of a presentation that spur a greater amount or durationof discussion can generally be considered more important, confusing,interesting, etc., than other parts of the presentation associated withdialogue of a lesser amount or of a shorter duration. Accordingly, thecontent classification component 110 can classify parts of apresentation associated with relatively high amounts or long duration ofdialogue as being particularly confusing, interesting or important. Inanother implementation, the content classification component 110 canfurther identify a number of questions respectively associated withdifferent parts of a presentation. For example, parts of a presentationassociated with a greater amount of questions relative to other parts ofthe presentation can generally be considered more confusing orinteresting. Accordingly, the content classification component 110 canclassify parts of a presentation associated with relatively high amountsof questions as being particularly confusing, interesting or important.Thus content classification component 110 can further correlate mentalstates of presentees with respective parts of the presentationassociated with dialogue, relatively long durations of dialogue, and/orrelatively high amounts of questions, to further determine a degree towhich the presentees considered the respective parts confusing,interesting, boring, exciting, amusing, etc.

Using the information determined by the analysis component 106, theindex component 114 can generate an index for the presentation thatidentifies respective parts of the presentation and the classificationsassociated with the parts of the presentation. In various embodiments,this index is referred to herein as a classification index. For example,the classification index 122 can include, but is not limited to:information identifying respective parts of a presentation, one or morekeywords associated with the respective parts, one or more slidesassociated with the respective parts (e.g., when the presentationincludes a slideshow), a particular aspect or elements of a single slideassociated with the respective parts, one or more classifications of therespective parts, values or scores associated with the classifications,and/or one or more user traits or preferences associated with therespective classifications. In various implementations, theclassification index 122 can be stored in memory 120 and employed by thepresentation server device 102 to facilitate associating auxiliaryinformation with the respective parts of the presentation and laterproviding the auxiliary information to new users when the presentationis later presented to the new users (and those new users need or desireauxiliary information).

FIG. 2 presents a table of an example, non-limiting contentclassification index 200 for a media presentation in accordance with oneor more embodiments described herein. Repetitive description of likeembodiments employed in respective embodiments is omitted for sake ofbrevity. The classification index 200 was generated by index component114. The classification index 200 can be provided for a presentationtitled “Ionic Bonding” and can include content classificationinformation for respective parts of the presentation generated based onfeedback received in association with presentation of the presentationto a group of users. For example, in one implementation, thepresentation was prepared by a teacher and presented to a group ofstudents in a live setting. The presentation includes 10 defined topicsassociated with 7 prepared slides. The classification index 200 includesinformation identifying various topics and the respective slides withwhich the topics are associated.

The classification index 200 can also include keywords associated withthe topics. In some implementations, the keywords were detected viaanalysis of speech spoken during the presentation (e.g., by thepresenter) using voice recognition hardware and software (e.g., providedat the user device or the presentation server device 102) to facilitateidentifying the current topic being presented. The classification index200 further includes classification categories “confusing” and“interesting.” Each topic can be associated with either a score or valueindicating a degree to which the topic was considered confusing orinteresting or the value “n/a” indicating that little or no usersconsidered the topic confusing or interesting. For example, as shown inclassification index 200, little or no users considered topic 1confusing or interesting.

In an aspect, the index component 114 can employ a threshold requirementto determine whether to associate a value of “n/a” with a topicclassification. For example, the index component 114 can associate “n/a”with a topic when less than N users found the topic confusing orinteresting. Also, in the embodiment shown, some of the topics wereconsidered confusing to some users yet interesting to others while othertopics were classified as either confusing or interesting, but not both.In one implementation, the number value associated with a topicclassification can reflect the number of users that considered the topicconfusing or interesting, respectively.

FIG. 3 illustrates a block diagram of an example, non-limiting userdevice 300 that facilitates classifying content of a media presentationand generating auxiliary information for the content in accordance withone or more embodiments described herein. In various embodiments, userdevice 300 can be or include a user device of the one or more userdevices 126 presented in system 100. Repetitive description of likeembodiments employed in respective embodiments is omitted for sake ofbrevity.

User device 300 can include an input device 302, client feedbackcomponent 312, client communication component 314, rendering component316 and a display 320. The user device 300 can also include or otherwisebe associated with at least one memory 324 that storescomputer-executable components (e.g., the client feedback component 312,the client communication component 314, and the rendering component316). The user device 300 can also include or otherwise be associatedwith at least one processor 322 that executes the computer-executablecomponents stored in the memory 120. The user device 300 can furtherinclude a device bus 318 that can couple the various componentsincluding, but not limited to, the input device 302, the client feedbackcomponent 312, the client communication component 314, the display 320,the memory 324 and/or processor 322. In one or more embodiments, theclient feedback component 312 can receive and/or process user feedbackinformation regarding an interest or desire for auxiliary contentassociated with a presentation. For example, the client feedbackcomponent 312 can receive feedback information regarding a mental stateof a user associated with user device 300 during a presentation. In someimplementations, such user feedback can be captured by the user device300 via an input device 302 provided at the user device. For example,the input device 302 can include, but is not limited to, a camera 304,an audio capture device 306, one or more motion sensors 308 and/or oneor more biometric sensors 310. In one implementation, the camera 304 canbe a user facing camera that captures imagery (e.g., video and/or stillimages) of the user's face during a presentation. In some embodiments,the camera 304 can also capture video and/or images of the user that canbe processed to detect and identify motion of the user (e.g., blinkingof eyes, nodding of head, etc.). The audio capture device 306 caninclude a microphone or another type of audio capture device that canreceive and record audio during a presentation, such as speech spoken bythe user associated with user device 300, speech of a presenter of thepresentation, dialogue between the user and the presenter, and/ordialogue between the user and another user. In some implementations, theaudio capture device 306 can further process captured audio to convertdetected speech to text. The one or more motion sensors 308 can include,for example, an accelerometer and/or a gyroscope that can detect motionof the user device 300 when worn, held or otherwise operated by theuser. The one or more biometric sensors 310 can include biometricsensors that detect biometric information for the user during apresentation, including, but not limited to, heart rate, respiratoryrate, and hormone levels of the user. In some implementations, one ormore of the motion sensors 308 and/or the biometric sensors 310 can beexternal to the user device 300 (e.g., worn by the user, implantedwithin the user, etc.) and communicatively coupled to the user device300.

In some embodiments, feedback information captured via the input device302 can be received and processed by the client feedback component 312to determine a mental state of the user based on the feedback. Forexample, the client feedback component 312 can determine a mental stateof the user based on analysis of one or more facial expressions includedin imaged data captured via the camera, based on analysis of tone ofvoice and words spoken in speech of the user captured via audio capturedevice 306, based on analysis of motion data regarding body language ofthe user captured via the one or more motion sensors 308, and/or basedon analysis of biometric data for the user captured via the one or morebiometric sensors 310. According to these embodiments, the clientcommunication component 314 can send (e.g., in real-time orsubstantially real-time) the processed feedback data identifying amental state of the user to the presentation server device 102 tofacilitate receiving auxiliary information from the presentation serverdevice 102. In other embodiments, the client communication component 314can send (e.g., in some embodiments, in real-time or substantiallyreal-time) the presentation server device 102 raw feedback informationcaptured via the input device 302 for processing by the server feedbackcomponent 104. The client communication component 314 can include sameor similar features and functionalities as server communicationcomponent 116. For example, in one or more embodiments, the clientcommunication component 314 can include hardware and/or software thatfacilitate wired or wireless communication between the user device 300and the presentation server device 102, and between the user device 300and one or more other external devices (not shown).

In some embodiments, the client feedback component 312 can also receiveexplicit input (e.g., via the input device 302) indicating a mentalstate of the user and/or a desire for a type of auxiliary informationassociated with a presentation. For example, using an input mechanismprovided by the input device 302, the user can generate a defined signalthat indicates the user is confused, interested, bored, etc. at anygiven time during a presentation. Similarly, the user can provide inputthat includes an explicit request for a type of auxiliary information(e.g., “please provide me with clarifying information on this topic”).It should be appreciated that the input mechanism can vary. For example,the user can provide speech input, motion gesture input (e.g., blinkingof eye, nodding of head, tapping of foot, raising of hand, etc.), aswell as input via a hard or soft button, a keypad, a touch screen, amouse, etc. The client feedback component 312 can also receive suchexplicit input and the client communication component 314 can providethis explicit input to the presentation server device 102.

FIG. 4 illustrates a block diagram of an example, non-limiting system400 that facilitates classifying content of a media presentation andgenerating auxiliary information for the content in accordance with oneor more embodiments described herein. System 400 includes same orsimilar features as system 100 with the addition of auxiliaryinformation component 402, application component 404 and auxiliaryinformation database 406. Repetitive description of like elementsemployed in respective embodiment is omitted for sake of brevity. Afterthe index component 114 generates a classification index for apresentation, in various embodiments, the auxiliary informationcomponent 402 can facilitate generating and associating auxiliaryinformation with respective parts of a presentation based on theinformation included in the classification index. For example, asdiscussed above, the classification index 122 associated with apresentation can include, but is not limited to: information identifyingrespective parts of a presentation, one or more keywords associated withthe respective parts, one or more slides associated with the respectiveparts (e.g., when the presentation includes a slideshow), a particularaspect or elements of a single slide associated with the respectiveparts, one or more classifications of the respective parts, values orscores associated with the classifications, and/or one or more usertraits or preferences associated with the respective classifications.

In various embodiments, the application component 404 can receiveauxiliary information for a part of a presentation and associate theauxiliary information with the part of the presentation that it wasprovided for. The auxiliary information can include, but is not limitedto, text, images, charts, audio, video, and/or hyperlinks thatassociated with and related to a particular part of a presentation. Theterm auxiliary information “data entry” is used herein to refer to theauxiliary information that is associated with a defined part of apresentation and in some implementations, a defined type and/or versionof auxiliary information. In one or more embodiments, various types ofauxiliary information can be associated with defined mental states. Forexample, in some implementations, auxiliary information intended tofacilitate helping a user better understand a part of the presentationabout which the user is confused can be referred to herein as“clarifying” auxiliary information. In another example, auxiliaryinformation intended to provide a user more detailed information orexamples about a part of the presentation a user is particularlyinterested in or intrigued by is referred to herein as “supplementary”auxiliary information. In another example, auxiliary informationintended to get a user's attention, (e.g., when the user providesfeedback indicating the user is bored or uninterested), is referred toherein as “attention” auxiliary information. It should be appreciatedthat the above described auxiliary information types are merelyexemplary and other types of auxiliary information related to differentmental states, purposes, and/or content types are also envisioned.

In addition to having different types of auxiliary information fordifferent mental states, different auxiliary information can also beassociated with different user profiles associated with defined usertraits and preferences. For example, with regards to educationalpresentations, user profile information can include, but is not limitedto, information regarding a user's intellectual level or capability,grades, learning type (e.g., visual, mathematical, kinesthetic,auditory, etc.), reading level or speed of the user, degree ofbackground knowledge in the presentation subject matter, multitaskingability, and the like. Thus in various embodiments, in addition tohaving different types of auxiliary information for different mentalstates, different versions of auxiliary information of a same type(e.g., clarifying, supplementary, attention, etc.) can be provided for asame part of content included in a presentation, wherein the differentversions are associated with defined user traits and/or preferences. Thedifferent versions for example can include different types of content(e.g., text, vs. images or video), different amounts of content,different degrees of content complexity, and the like. For example, afirst version of clarifying auxiliary information regarding how twomolecules bind can include a visual animation includingthree-dimensional models of the two molecules demonstrating how theybind, and second version of clarifying auxiliary information regardinghow the two molecules bind can include chemical formulas of the twomolecules when separated and when combined. According to this example,the first version of the clarifying information can be provided for avisual learner with a basic chemical background while the second versioncan be provided for mathematical learner with a more complex chemicalbackground. In another example, a first version of supplementaryauxiliary content that is intended for presentation to a slow reader caninclude less textual information relative to a second version of thesupplementary auxiliary content that is intended for presentation to afast reader.

In some embodiments, the application component 404 can receive theauxiliary information from the presenter of the presentation or anthersuitable entity responsible for providing auxiliary information for thepresentation. For example, in various implementations, the applicationcomponent 404 can facilitate entry of auxiliary information via aninteractive presentation application provided by the presentation serverdevice 102 that facilitates generating presentations (e.g., slideshows,outlines, etc.), reviewing feedback received for a presentation,reviewing a classification index generated for a presentation,generating and applying auxiliary information to a presentation,refining auxiliary information applied to the presentation or the like.For example, the interactive presentation application can be providedvia a website platform accessible via one or more networks 124, deployedas a dedicated application on a device accessible to the presenter(e.g., the presenter's laptop computer, work desktop computer, etc.),deployed as a thin client application on the device accessible to thepresenter, deployed as a thick client application on the deviceaccessible to the presenter, and the like.

In one or more embodiments, the presentation server device 102 canprovide the presenter (or another suitable entity responsible forproviding auxiliary content for the presentation) with theclassification index generated for a presentation or the informationincluded in the classification index (e.g., via the server communicationcomponent 116, via the interactive presentation application, etc.).Using the interactive presentation application or another suitable dataentry mechanism, the presenter of the presentation (or another suitableentity responsible for providing auxiliary content for the presentation)can review and evaluate the classification information and decide forwhich parts of the presentation to provide auxiliary information, a typeof auxiliary information to provide and/or a version of auxiliaryinformation to provide. For example, the presenter can receive andreview the information in the classification index and learn informationregarding what parts of the presentation users found confusing,interesting, boring, exciting, amusing, etc. and a degree to which theusers found the part of the presentation confusing, interesting, boring,exciting, amusing, etc. The presenter can then choose to provide anappropriate type of auxiliary information for the respective parts ofthe presentation. For example, the presenter can select a part of thepresentation to associate with auxiliary information and generate anauxiliary information data entry for the part including text, images,audio, video, hyperlinks, etc. The application component 404 can furtherstore the auxiliary information data entry in an auxiliary informationdatabase 406 and associate the auxiliary information data entry with theselected part of the presentation. In some implementations, thepresenter can also employ classification information indicating userprofile characteristics associated with a classification to tailor theauxiliary information to the profile type. For example, based onclassification information indicating many visual learners in the classwere confused about topic 2 of the presentation, the presenter cangenerate clarifying information that includes pictorial examples thathelp to explain topic 2.

In the embodiments described above, the application component 404 canprovide a presenter with the classification index information generatedfor a presentation and can allow the presenter to manually evaluate theclassification information to decide whether to provide auxiliaryinformation for a part of the content, a type of the auxiliaryinformation and/or a version of the auxiliary information. In anotherembodiment, the application component 404 can analyze the classificationinformation to automatically output information identifying parts of thepresentation for which to provide auxiliary information, a type of theauxiliary information and/or a version of the auxiliary information.According to this embodiment, the application component 404 can employdefined threshold requirements regarding a degree to which a part of thepresentation was considered confusing, interesting, boring, exciting,amusing, etc., to identify one or more parts of the presentation forassociation with auxiliary information. For example, the applicationcomponent 404 can identify one or more parts of a presentationassociated with a classification score of X or above and recommend theseone or more parts for association with auxiliary information. Thecontent classification component 110 can further output informationidentifying these one or more parts of the presentation, a typeauxiliary information to provide for one or more parts as determined bythe application component 404 based on the classification associatedwith the one or more parts (e.g., clarifying, supplementary, etc.)and/or a version of the auxiliary information to provide for the one ormore parts as determined by the application component 404. Theapplication component 404 can make such determinations based on usertraits and preferences associated with the classification of the parts(e.g., short, long, simple, complex, image based, math based, etc) insome embodiments. According to this embodiment, the presenter can spendless time manually reviewing the classification information and generateauxiliary information for only the most relevant parts of thepresentation.

After auxiliary information entries are received for respective parts ofa presentation and stored in the auxiliary information database 406, theindex component 114 can further generate an auxiliary information index408 that includes information identifying, the presentation and thedefined parts (e.g., topics, sub-topics, elements, etc.) of thepresentation. The auxiliary information index 408 can further includeinformation identifying auxiliary information entries (e.g., included inauxiliary information database 406) respectively associated with one ormore parts of the presentation, a type of the auxiliary information, aversion of the auxiliary information, and/or a user profile trait orpreference associated with the auxiliary information. In someembodiments in which the presentation includes slides, the auxiliaryinformation index 408 can include information identifying respectiveslides associated with each part of the presentation. Similarly, in someembodiments in which the presentation includes a video, the auxiliaryinformation index can include information identifying time points ortime frames of the video associated with one or more parts of thepresentation. In other embodiments in which the presentation includesspeech, the auxiliary information index can include keywordsrespectively associated with different parts of the presentation. Theauxiliary information index 408 can be stored in memory 120 or otherwisebe made accessible to the presentation server device 102.

FIG. 5 presents a table of an example, non-limiting auxiliaryinformation index 500 for a media presentation in accordance with one ormore embodiments described herein. The auxiliary information index 500is provided for a presentation titled “Ionic Bonding” including 10defined topics respectively associated with 7 prepared slides. In one ormore embodiments, the auxiliary information index 500 was generated bythe index component 114 based in part on the classification index 200generated for the presentation and auxiliary information received forthe presentation. For example, in the embodiment shown, the topicsidentified in classification index 200 having the value “n/a” associatedwith the confusing classification and/or the interesting classificationdo not include auxiliary information entries for the correspondingcategories, clarifying and supplementary, respectively. Repetitivedescription of like elements employed in respective embodiments isomitted for sake of brevity.

The auxiliary information index 500 can include information one or moretopics and the respective slides associated with one or more topics. Theauxiliary information index 500 further includes keywords associatedwith one or more topics. In addition, the auxiliary information index500 includes information identifying auxiliary information respectivelyassociated with one or more topics. In the embodiment shown, theauxiliary information can include two types of auxiliary information,clarifying auxiliary information and supplementary auxiliaryinformation. Further each type of auxiliary information can have entriesfor a first version and a second version of the respective types ofauxiliary information. For example, the first versions of the clarifyingand supplementary auxiliary information can be intended for provision tostudents that are visual learners and the second versions of theclarifying and supplementary auxiliary information can be intended forprovision to students that are mathematical learners. Each auxiliaryinformation entry is associated with a unique identifier (e.g., C-103,C-104, S-105, S-106). These identifiers can facilitate identifying andretrieving the corresponding auxiliary information in the auxiliaryinformation database 406 for providing to a new user based on newfeedback received from the new user during presentation of the ionicbonding presentation to the new user (as described infra with referenceto FIG. 6). For example, in response to a determination that Donna, avisual learner student, is confused in association with presentation oftopic 8, the auxiliary information component 402 can retrieve theauxiliary information associated with identifier C-116 and provide thisauxiliary information to Donna. Likewise, in response to a determinationthat Erin, a mathematical learner student, is particularly interested intopic 5, the auxiliary information component 402 can retrieve theauxiliary information associated with identifier S-110 and provide thisauxiliary information to Erin.

FIG. 6 illustrates a block diagram of another example, non-limitingsystem 600 that facilitates generating auxiliary information for a mediapresentation and conditional provisioning of the auxiliary informationin accordance with one or more embodiments described herein. System 600includes same or similar features as system 400 with the addition ofselection component 602 to the auxiliary information component 402.Repetitive description of like elements employed in respectiveembodiment is omitted for sake of brevity. In various embodiments, afterauxiliary information has been provided for a presentation and the indexcomponent 114 has generated an auxiliary information index 408 for thepresentation, the selection component 602 can employ the auxiliaryinformation index 408 to automatically select and provide auxiliaryinformation to new users when the presentation is subsequently presentedto the new users (e.g., either in a live context or during playback of arecording of the presentation). In particular, when the presentation issubsequently presented to a new user, the server feedback component 104can receive new feedback regarding a mental state of the new user and/oran explicit desire for auxiliary information as the new user is viewing,listening to or otherwise experiencing the presentation. The type offeedback and the manner in which it is generated and received by theserver feedback component 104 can include the same or similar type offeedback generated and received in a same or similar manner as thatdiscussed with reference to FIG. 1. Based on reception of the newfeedback, the content association component 108 can identify a part ofthe presentation associated with the new feedback (e.g., a definedtopic, sub-topic, element, etc.) in a same or similar manner as thatdiscussed with reference to FIG. 1 and system 100.

The selection component 602 can further select auxiliary information toprovide to the new user at the user's user device based on the newfeedback and the part of the presentation associated with the newfeedback, as identified in the auxiliary information index 408associated with the presentation. For example, based on informationreceived and/or determined by the server feedback component 104identifying a mental state of the new user or providing an explicitrequest for a type of auxiliary information, information determined bycontent association component 108 identifying a specific part of thepresentation associated with a cause of the mental state of the user,and/or information regarding a known trait (e.g., intellectual level,learning type, etc.) and/or preference of the user, the selectioncomponent 602 can employ the auxiliary information index 408 toidentify, determine or select the appropriate auxiliary information(e.g., included auxiliary information database 406) for providing to thenew user. For example, based on reception of user feedback informationindicating the user has a confused mental state in association withpresentation of topic 2 of a presentation, the selection component 602can access and employ the auxiliary information index 408 to determinewhether clarifying auxiliary information has been provided for topic 2in the auxiliary information database 406. In response to adetermination that clarifying information has been provided for topic 2,the selection component 602 can retrieve the auxiliary information andthe auxiliary information component 402 can provide (e.g., using servercommunication component 116) the auxiliary information to the userdevice of the new user (e.g., a user device of the one or more userdevices 126 or another device) for rendering at the user device.Further, in an embodiment in which different versions of the auxiliaryinformation associated with different user traits or preferences areprovided, the selection component 602 can determine one or more traitsand/or preferences of the user and select the version of the auxiliaryinformation that is best suited for the user based on the user's traitsand/or preferences. For example, if the user is a visual learner, theselection component 602 can select the version of the auxiliaryinformation for topic 2 that is associated with visual learning.

In one or more embodiments, the auxiliary information component 402 canprovide (e.g., using server communication component 116) selectedauxiliary information associated with a part of a presentation to a userdevice (e.g., a user device of the one or more user devices 126 oranother device) of a user in real-time or substantially real-time as thefeedback is received for the user and the part of the presentation isbeing presented. The user device can further render the auxiliaryinformation in association with presentation of the part of thepresentation (e.g., as the part is discussed in a live context, as thepart is presented in a live-context, as the part is presented or playedin a slideshow or video in a live or non-live context, etc.). Forexample, if the auxiliary information is associated with a particulartopic being presented, the user device can render the auxiliaryinformation while the topic is being presented. In other embodiments,the auxiliary information can be rendered at a later time, such asduring a break period after the topic is discussed or after the entirepresentation is finished. With reference to FIGS. 3 and 6, the userdevice 300 can include rendering component 316 to render auxiliaryinformation received from the presentation server device 102. Forexample, in an embodiment in which the auxiliary information includesaudio, the rendering component 316 can cause the audio to be played atthe user device 300 via a speaker of the user device (e.g., not shown).In another example, in an embodiment in which the auxiliary informationincludes visual data (e.g., text, images, video, hyperlinks, etc.) therendering component 316 can generate a graphical user interface that canbe displayed via the display 320 of the user device 300 and includingreceived auxiliary information. The manner in which the auxiliaryinformation is rendered at the user device can vary depending on thefeatures and functionalities of the user device.

FIG. 7 illustrates a block diagram of an example, non-limiting system700 that facilitates refining auxiliary information generated for amedia presentation in accordance with one or more embodiments describedherein. System 700 includes same or similar features as system 600 withthe addition of refinement component 702. Repetitive description of likeelements employed in respective embodiment is omitted for sake ofbrevity. In various scenarios, a presentation can be re-presented manytimes to new users and audiences. For example, after presenting alecture to a first class of students, a teacher can present the samelecture to a second, third, fourth, etc., class of students. In anotherexample, a presentation that includes an audio recording for a walkingtour of a museum, historic building, city landmarks, etc., can be playedback many times to new visitors. In another example, a presentation thatincludes a recorded video can be accessed and played back to new viewerson-demand any number of times. In view of these scenarios, therefinement component 702 can employ machine learning techniques tofacilitate refining and improving classifications of respective parts ofa presentation and/or auxiliary information associated with therespective parts of the presentation over time based on new userfeedback received each time the presentation is re-presented to one ormore new presentees.

For example, in some embodiments, when a presentation is re-presented toa new user and new feedback is received regarding respective mentalstates of the new user toward respective parts of the presentation, theanalysis component 106 can determine and associate new information withthe respective parts of the presentation regarding whether and to whatdegree the new user is confused, interested, bored, excited, amused,etc., with the respective parts of the presentation. As such newfeedback is collected and received from more and more new users, therefinement component 702 can direct the classification component tore-classify the respective parts of the presentation based on acompilation of the initial feedback for which the initial classificationwas made and the new feedback. As classifications associated withrespective parts of a presentation become more precise, the refinementcomponent 702 can determine one or more parts of the presentation thatmay need new auxiliary information and/or modified auxiliary informationbased on a degree of change associated with the classification of theone or more parts.

The refinement component 702 can employ a similar mechanism to determinewhether auxiliary information associated with a part of a presentationis helpful or otherwise well received by a user. For example, when apresentation is re-presented to a new user and auxiliary information fora part of the presentation is rendered to the new user, the serverfeedback component 104 can receive additional feedback from the new userregarding the new user's impression of the auxiliary information. Forinstance, the additional feedback can include information regarding amental state of the user responsive to the auxiliary information asdetermined based on facial expression data, speech data, body movementdata, biometric data, etc., received for the new user duringpresentation of the auxiliary information to the new user. Theadditional feedback can also include explicit feedback provided by thenew user regarding the new user's impression of the auxiliaryinformation. For example, in association with presentation of auxiliaryinformation, a prompt can be presented to the new user asking the userto provide input selecting “yes” or “no” to indicate whether the userfound the auxiliary information useful, interesting, amusing, etc.(e.g., or another intended impression for the particular auxiliaryinformation). The refinement component 702 can therefore gatheradditional feedback information regarding the impressions the respectiveauxiliary information entries have on one or more new users. In someembodiments, the refinement component 702 can user this additionalfeedback information to identify auxiliary information entries that arewell received (e.g., are associated with a favorable impression) andthose that are not well received (e.g., are associated with anunfavorable impression). For example, in some embodiments, therefinement component 702 can score the respective auxiliary informationentries based on a degree to which they are respectively associated withfavorable and/or unfavorable feedback. The refinement component 702 canfurther identify outliers in the unfavorable direction. For example, therefinement component 702 can identify one or more auxiliary informationentries associated with a score reflective of an unfavorable or highlyunfavorable (e.g., with respect to a threshold score) user impression.The refinement component 702 can further generate and provide arecommendation (e.g., to the presenter or another entity responsible forrevising auxiliary information for the presentation) identifying the oneor more auxiliary information entries associated with the unfavorablescore and suggesting modification or refinement of the one or moreauxiliary information entries.

FIG. 8 illustrates a flow diagram of an example, non-limitingcomputer-implemented method 800 that facilitates classifying content ofa media presentation in accordance with one or more embodimentsdescribed herein. Repetitive description of like embodiments employed inrespective embodiments is omitted for sake of brevity. At 802, a deviceoperatively coupled to a processor (e.g., presentation server device102) receives feedback information for a group of users regarding mentalstates of the users during a media presentation (e.g., via serverfeedback component 104). At 804, the device determines levels ofconfusion associated with respective parts of the presentation andlevels of interest associated with the respective parts of thepresentation based on the first feedback information (e.g., via contentassociation component 108). At 806, the device classifies first parts ofthe respective parts of the presentation as confusing based on thelevels of confusion associated with the first parts being above athreshold level of confusion (e.g., via content classification component110). At 808, the device classifies second parts of the respective partsof the presentation as interesting based on the levels of interestassociated with the second parts being above a threshold level ofinterest (e.g., via content classification component 110).

FIG. 9 illustrates a flow diagram of an example, non-limitingcomputer-implemented method 900 that facilitates classifying content ofa media presentation in accordance with one or more embodimentsdescribed herein. Repetitive description of like embodiments employed inrespective embodiments is omitted for sake of brevity. At 902, a deviceoperatively coupled to a processor (e.g., presentation server device102), receives feedback information for a group of users regardingmental states of the users during a media presentation (e.g., via serverfeedback component 104). At 904, the device determines first parts ofthe media presentation considered confusing to at least some of theusers and second parts of the media presentation considered interestingto at least some of the users based on the feedback information (e.g.,via content association component 108). At 906, the device classifiesthe first parts as interesting and the second parts as interesting(e.g., via content classification component 110). At 908, the devicereceives respective clarifying information data entries for the firstparts, and respective supplementary information data entries for thesecond parts (e.g., via application component 404). At 910, the deviceassociates the respective clarifying information data entries with thefirst parts in an auxiliary information index data structure, and therespective supplementary information data entries with the second partsin the auxiliary information index data structure (e.g., via indexcomponent 114). At 912, the device employs the auxiliary informationindex data structure during presentation of the media presentation to anew user to select at least one of the respective clarifying informationdata entries or at least one of the respective supplementary informationdata entries for providing to a user device of the new user based onthird feedback information received from the user device during thepresentation of the media presentation indicative of the new user'sunderstanding of at least one of the first parts or interest in at leastone of the second parts.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 10 as well as the following discussion are intendedto provide a general description of a suitable environment in which thevarious aspects of the disclosed subject matter can be implemented. FIG.10 illustrates a block diagram of an example, non-limiting operatingenvironment in which one or more embodiments described herein can befacilitated. Repetitive description of like elements employed in otherembodiments described herein is omitted for sake of brevity. Withreference to FIG. 10, a suitable operating environment 1001 forimplementing various aspects of this disclosure can also include acomputer 1012. The computer 1012 can also include a processing unit1014, a system memory 1016, and a system bus 1018. The system bus 1018couples system components including, but not limited to, the systemmemory 1016 to the processing unit 1014. The processing unit 1014 can beany of various available processors. Dual microprocessors and othermultiprocessor architectures also can be employed as the processing unit1014. The system bus 1018 can be any of several types of busstructure(s) including the memory bus or memory controller, a peripheralbus or external bus, and/or a local bus using any variety of availablebus architectures including, but not limited to, Industrial StandardArchitecture (ISA), Micro-Channel Architecture (MSA), Extended ISA(EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus(USB), Advanced Graphics Port (AGP), Firewire (IEEE 1094), and SmallComputer Systems Interface (SCSI). The system memory 1016 can alsoinclude volatile memory 1020 and nonvolatile memory 1022. The basicinput/output system (BIOS), containing the basic routines to transferinformation between elements within the computer 1012, such as duringstart-up, is stored in nonvolatile memory 1022. By way of illustration,and not limitation, nonvolatile memory 1022 can include read only memory(ROM), programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), flash memory, ornonvolatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM).Volatile memory 1020 can also include random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as static RAM (SRAM),dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM(DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), directRambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and Rambusdynamic RAM.

Computer 1012 can also include removable/non-removable,volatile/nonvolatile computer storage media. FIG. 10 illustrates, forexample, a disk storage 1024. Disk storage 1024 can also include, but isnot limited to, devices like a magnetic disk drive, floppy disk drive,tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, ormemory stick. The disk storage 1024 also can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage 1024 to the system bus 1018, a removableor non-removable interface is typically used, such as interface 1026.FIG. 10 also depicts software that acts as an intermediary between usersand the basic computer resources described in the suitable operatingenvironment 1001. Such software can also include, for example, anoperating system 1028. Operating system 1028, which can be stored ondisk storage 1024, acts to control and allocate resources of thecomputer 1012. System applications 1030 take advantage of the managementof resources by operating system 1028 through program modules 1032 andprogram data 1034, e.g., stored either in system memory 1016 or on diskstorage 1024. It is to be appreciated that this disclosure can beimplemented with various operating systems or combinations of operatingsystems. A user enters commands or information into the computer 1012through input device(s) 1036. Input devices 1036 include, but are notlimited to, a pointing device such as a mouse, trackball, stylus, touchpad, keyboard, microphone, joystick, game pad, satellite dish, scanner,TV tuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processing unit 1014through the system bus 1018 via interface port(s) 1038. Interfaceport(s) 1038 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1040 usesome of the same type of ports as input device(s) 1036. Thus, forexample, a USB port can be used to provide input to computer 1012, andto output information from computer 1012 to an output device 1040.Output adapter 1042 is provided to illustrate that there are some outputdevices 1040 like monitors, speakers, and printers, among other outputdevices 1040, which require special adapters. The output adapters 1042include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1040and the system bus 1018. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1044.

Computer 1012 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1044. The remote computer(s) 1044 can be a computer, a server, a router,a network PC, a workstation, a microprocessor based appliance, a peerdevice or other common network node and the like, and typically can alsoinclude many or all of the elements described relative to computer 1012.For purposes of brevity, only a memory storage device 1046 isillustrated with remote computer(s) 1044. Remote computer(s) 1044 islogically connected to computer 1012 through a network interface 1048and then physically connected via communication connection 1050. Networkinterface 1048 encompasses wire and/or wireless communication networkssuch as local-area networks (LAN), wide-area networks (WAN), cellularnetworks, etc. LAN technologies include Fiber Distributed Data Interface(FDDI), Copper Distributed Data Interface (CDDI), Ethernet, Token Ringand the like. WAN technologies include, but are not limited to,point-to-point links, circuit switching networks like IntegratedServices Digital Networks (ISDN) and variations thereon, packetswitching networks, and Digital Subscriber Lines (DSL). Communicationconnection(s) 1050 refers to the hardware/software employed to connectthe network interface 1048 to the system bus 1018. While communicationconnection 1050 is shown for illustrative clarity inside computer 1012,it can also be external to computer 1012. The hardware/software forconnection to the network interface 1048 can also include, for exemplarypurposes only, internal and external technologies such as, modemsincluding regular telephone grade modems, cable modems and DSL modems,ISDN adapters, and Ethernet cards.

Embodiments of the present invention may be a system, a method, anapparatus and/or a computer program product at any possible technicaldetail level of integration. The computer program product can include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present invention. The computer readable storage mediumcan be a tangible device that can retain and store instructions for useby an instruction execution device. The computer readable storage mediumcan be, for example, but is not limited to, an electronic storagedevice, a magnetic storage device, an optical storage device, anelectromagnetic storage device, a semiconductor storage device, or anysuitable combination of the foregoing. A non-exhaustive list of morespecific examples of the computer readable storage medium can alsoinclude the following: a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), a static randomaccess memory (SRAM), a portable compact disc read-only memory (CD-ROM),a digital versatile disk (DVD), a memory stick, a floppy disk, amechanically encoded device such as punch-cards or raised structures ina groove having instructions recorded thereon, and any suitablecombination of the foregoing. A computer readable storage medium, asused herein, is not to be construed as being transitory signals per se,such as radio waves or other freely propagating electromagnetic waves,electromagnetic waves propagating through a waveguide or othertransmission media (e.g., light pulses passing through a fiber-opticcable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network can comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device. Computer readable programinstructions for carrying out operations of various aspects of thepresent invention can be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions can executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer can be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection can be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) can execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to customize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions. These computer readable programinstructions can be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks. These computer readable program instructions can also be storedin a computer readable storage medium that can direct a computer, aprogrammable data processing apparatus, and/or other devices to functionin a particular manner, such that the computer readable storage mediumhaving instructions stored therein comprises an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks. Thecomputer readable program instructions can also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational acts to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams can represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks can occur out of theorder noted in the Figures. For example, two blocks shown in successioncan, in fact, be executed substantially concurrently, or the blocks cansometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While the subject matter has been described above in the general contextof computer-executable instructions of a computer program product thatruns on a computer and/or computers, those skilled in the art willrecognize that this disclosure also can or can be implemented incombination with other program modules. Generally, program modulesinclude routines, programs, components, data structures, etc. thatperform particular tasks and/or implement particular abstract datatypes. Moreover, those skilled in the art will appreciate that theinventive computer-implemented methods can be practiced with othercomputer system configurations, including single-processor ormultiprocessor computer systems, mini-computing devices, mainframecomputers, as well as computers, hand-held computing devices (e.g., PDA,phone), microprocessor-based or programmable consumer or industrialelectronics, and the like. The illustrated aspects can also be practicedin distributed computing environments where tasks are performed byremote processing devices that are linked through a communicationsnetwork. However, some, if not all aspects of this disclosure can bepracticed on stand-alone computers. In a distributed computingenvironment, program modules can be located in both local and remotememory storage devices.

As used in this application, the terms “component,” “system,”“application,” “platform,” “interface,” and the like, can refer toand/or can include a computer-related entity or an entity related to anoperational machine with one or more specific functionalities. Theentities disclosed herein can be either hardware, a combination ofhardware and software, software, or software in execution. For example,a component can be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and/or a computer. By way of illustration, both anapplication running on a server and the server can be a component. Oneor more components can reside within a process and/or thread ofexecution and a component can be localized on one computer and/ordistributed between two or more computers. In another example,respective components can execute from various computer readable mediahaving various data structures stored thereon. The components cancommunicate via local and/or remote processes such as in accordance witha signal having one or more data packets (e.g., data from one componentinteracting with another component in a local system, distributedsystem, and/or across a network such as the Internet with other systemsvia the signal). As another example, a component can be an apparatuswith specific functionality provided by mechanical parts operated byelectric or electronic circuitry, which is operated by a software orfirmware application executed by a processor. In such a case, theprocessor can be internal or external to the apparatus and can executeat least a part of the software or firmware application. As yet anotherexample, a component can be an apparatus that provides specificfunctionality through electronic components without mechanical parts,wherein the electronic components can include a processor or other meansto execute software or firmware that confers at least in part thefunctionality of the electronic components. In an aspect, a componentcan emulate an electronic component via a virtual machine, e.g., withina cloud computing system.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form. As used herein, the terms “example”and/or “exemplary” are utilized to mean serving as an example, instance,or illustration. For the avoidance of doubt, the subject matterdisclosed herein is not limited by such examples. In addition, anyaspect or design described herein as an “example” and/or “exemplary” isnot necessarily to be construed as preferred or advantageous over otheraspects or designs, nor is it meant to preclude equivalent exemplarystructures and techniques known to those of ordinary skill in the art.

As it is employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Further, processors can exploit nano-scalearchitectures such as, but not limited to, molecular and quantum-dotbased transistors, switches and gates, in order to optimize space usageor enhance performance of user equipment. A processor can also beimplemented as a combination of computing processing units. In thisdisclosure, terms such as “store,” “storage,” “data store,” datastorage,” “database,” and substantially any other information storagecomponent relevant to operation and functionality of a component areutilized to refer to “memory components,” entities embodied in a“memory,” or components comprising a memory. It is to be appreciatedthat memory and/or memory components described herein can be eithervolatile memory or nonvolatile memory, or can include both volatile andnonvolatile memory. By way of illustration, and not limitation,nonvolatile memory can include read only memory (ROM), programmable ROM(PROM), electrically programmable ROM (EPROM), electrically erasable ROM(EEPROM), flash memory, or nonvolatile random access memory (RAM) (e.g.,ferroelectric RAM (FeRAM). Volatile memory can include RAM, which canact as external cache memory, for example. By way of illustration andnot limitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM),direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), andRambus dynamic RAM (RDRAM). Additionally, the disclosed memorycomponents of systems or computer-implemented methods herein areintended to include, without being limited to including, these and anyother suitable types of memory.

What has been described above include mere examples of systems andcomputer-implemented methods. It is, of course, not possible to describeevery conceivable combination of components or computer-implementedmethods for purposes of describing this disclosure, but one of ordinaryskill in the art can recognize that many further combinations andpermutations of this disclosure are possible. Furthermore, to the extentthat the terms “includes,” “has,” “possesses,” and the like are used inthe detailed description, claims, appendices and drawings such terms areintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim. The descriptions of the various embodiments have been presentedfor purposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiments. The terminologyused herein was chosen to best explain the principles of theembodiments, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

1. A system comprising: a memory that stores computer executablecomponents; a processor that executes computer executable componentsstored in the memory, wherein the computer executable componentscomprise: a feedback component that receives first feedback informationfor a group of users regarding mental states of the users during a firstpresentation of a media presentation, and second feedback informationcomprising dialogue recorded during the first presentation of the mediapresentation, wherein the dialogue is between a presenter of the mediapresentation and one or more users of the group of users; an analysiscomponent that determines first parts of the media presentationconsidered confusing to at least some of the users and second parts ofthe media presentation considered interesting to at least some of theusers based on the first feedback information and based on associationof the first parts or the second parts with the recorded dialogue; andan index component that generates an index data structure comprising:first information identifying the first parts and classifying the firstparts as confusing; and second information identifying the second partsand classifying the second parts as interesting.
 2. The system of claim1, wherein the first feedback information comprises informationindicative of facial expressions of the users, and wherein the analysiscomponent determines the first parts based on association of the firstparts with a subset of the facial expressions indicative of a mentalstate of confusion.
 3. The system of claim 1, wherein the first feedbackinformation comprises information indicative of facial expressions ofthe users, and wherein the analysis component determines the secondparts based on association of the second parts with a subset of thefacial expressions indicative of a mental state of intrigue. 4.(canceled)
 5. The system of claim 1, wherein the analysis componentfurther determines the first parts or the second parts based on a numberof questions asked during the recorded dialogue.
 6. The system of claim1, wherein the analysis component further determines the first parts orthe second parts based on whether a first portion of the recordeddialogue associated with the first parts or a second portion of therecorded dialogue associated with the second parts is greater induration.
 7. The system of claim 1, wherein the computer executablecomponents further comprise: an auxiliary information component thatreceives respective clarifying information data entries for the firstparts, and respective supplementary information data entries for thesecond parts.
 8. The system of claim 7, wherein the index componentfurther associates, in the index data structure, the respectiveclarifying information data entries with the first parts and therespective supplementary information data entries with the second parts.9. The system of claim 8, wherein the computer executable componentsfurther comprise: a selection component that employs the index datastructure during a second presentation of the media presentation toselect at least one of the respective clarifying information dataentries or at least one of the respective supplementary information dataentries to provide to a device based on third feedback informationreceived from a user of the device during the second presentation of themedia presentation.
 10. The system of claim 9, wherein the thirdfeedback information comprises information indicative of a level ofunderstanding of the first parts by the user or a level of interest inthe second parts by the user.
 11. The system of claim 8, wherein thecomputer executable components further comprise: a refinement componentthat scores the respective clarifying information data entries and therespective supplementary information data entries based on thirdfeedback information, received for a group of new users during a secondpresentation of the media presentation to the group of new users,regarding respective reactions of the new users to the respectiveclarifying information data entries and the respective supplementaryinformation data entries.
 12. The system of claim 11, wherein therefinement component further selects one or more of the respectiveclarifying information data entries or the respective supplementaryinformation data entries for modification based on association with ascore indicative of an unfavorable user reaction.
 13. Acomputer-implemented method, comprising: receiving, by a deviceoperatively coupled to a processor, first feedback information for agroup of users regarding mental states of the users during a firstpresentation of a media presentation; receiving, by the device, secondfeedback information comprising dialogue recorded during the firstpresentation of the media presentation, wherein the dialogue is betweena presenter of the media presentation and one or more users of the groupof users; determining, by the device, levels of confusion associatedwith respective parts of the presentation and levels of interestassociated with the respective parts of the presentation based on thefirst feedback information and based on association of respective partsof the recorded dialogue with the first parts or the second parts;classifying, by the device, first parts of the respective parts of thepresentation as confusing based on the levels of confusion associatedwith the first parts being above a threshold level of confusion; andclassifying, by the device, second parts of the respective parts of thepresentation as interesting based on the levels of interest associatedwith the second parts being above a threshold level of interest.
 14. Thecomputer-implemented method of claim 13, wherein the first feedbackinformation comprises information indicative of facial expressions ofthe users, the computer-implemented method further comprising:determining, by the device, the first parts based on association ofrespective first subsets of the facial expressions indicative of amental state of confusion with the first parts; and determining, by thedevice the second parts based on association of respective subsets ofthe facial expressions indicative of a mental state of intrigue with thesecond parts.
 15. (canceled)
 16. The computer-implemented method ofclaim 13, further comprising: receiving, by the device, respectiveclarifying information data entries for the first parts, and respectivesupplementary information data entries for the second parts; andgenerating, by the device, an index data structure comprising: firstinformation identifying the first parts, classifying the first parts asconfusing, and identifying the respective clarifying information dataentries with the first parts; and second information identifying thesecond parts, classifying the second parts as interesting, andidentifying the respective supplementary information data entries withthe second parts.
 17. The computer-implemented method of claim 16,further comprising: employing, by the device, the index data structureduring a second presentation of the media presentation to select atleast one of the respective clarifying information data entries or atleast one of the respective supplementary information data entries toprovide to a device of a user based on third feedback informationreceived from the user during the second presentation of the mediapresentation.
 18. A computer program for identifying respective parts ofa media presentation considered confusing or interesting, the computerprogram product comprising a computer readable storage medium havingprogram instructions embodied therewith, the program instructionsexecutable by a processing component to cause the processing componentto: identify, based on feedback information associated with a firstpresentation of the media presentation to users, first parts of themedia presentation considered confusing to at least some of the usersand second parts of the media presentation considered interesting to atleast some of the users, wherein the feedback information comprisesfacial expression information regarding facial expressions of the usersduring the first presentation of the media presentation and dialoguerecorded during the first presentation of the media presentation that isassociated with the first parts or the second parts, and wherein thedialogue is between a presenter of the media presentation and one ormore users of the users; and generate an index data structurecomprising: first information identifying the first parts and includingclarifying information for the first parts; and second informationidentifying the second parts and including supplementary information forthe second parts.
 19. The computer program product of claim 18, whereinthe program instructions executable by the processing component furthercause the processing component to: employ the index data structureduring a second presentation of the media presentation to provide atleast some of the clarifying information or at least some of thesupplementary information to a device of a new user based on newfeedback information received from the new user during the secondpresentation of the media presentation, thereby facilitating improvedprocessing time for selection and provision of auxiliary informationduring the second presentation of the media presentation.
 20. (canceled)